Simple Python library written in Rust for analyzing and scoping out patterns in time series data
Project description
TimeScope
Simple Python library written in Rust for analyzing and scoping out patterns in time series data. This is a pet project to practice programming in Rust and currently only contains two algorithms:
- ED-Pelt change point detection
- Steady State detection (based on change points)
Example Use
from timescope import TimeSeriesData, cpd_ed_pelt, ssd_cpd
A = [0, 0, 0, 0, 10, 10, 10, 10, 10, 0, 0, 0, 0]
B = list(range(len(A)))
cps = cpd_ed_pelt(A, 1)
print(f"change points: {cps}")
# change points: [4, 9]
ts = TimeSeriesData(B, A)
print(ts)
# TimeSeriesData(time=[0, 1, ..., 11, 12], data=[0, 0, ..., 0, 0], granularity=1, is_step=false)
resampled_ts = ts.equally_spaced_resampling()
print(resampled_ts.slice(3, 6))
# TimeSeriesData(time=[3, 4, 5, 6], data=[0, 10, 10, 10], granularity=1, is_step=false)
ss_map = ssd_cpd(resampled_ts, 1, 1.0, -1.0)
print(f"steady state map: {ss_map.data}")
# steady state map: [1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0]
Install
pip install timescope
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File details
Details for the file timescope-0.1.0-cp37-abi3-macosx_10_7_x86_64.whl.
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- Upload date:
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